DeepBurst: Predicting transcriptional burst kinetics from histone modifications with deep learning
Abstract
This record releases the processed datasets and pretrained DeepBurst model weights (checkpoints) for reproducing our experimental results and for downstream applications. DeepBurst is a deep-learning framework that leverages histone-modification features to predict transcriptional bursting–related phenotypes (e.g., classification/decision tasks for burst frequency and burst size, as defined in the manuscript).
Fields of Study & Subjects
Genomics and Chromatin Dynamics
Gene Regulatory Network Analysis
Single-cell and spatial transcriptomics
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 13 January 2026
- Language
- EN